我有一个人脸识别代码（在最后给出了完整的代码），它与现有数据集完美配合。
但我希望它在要求用户输入框架中新人的姓名后，也将新面孔添加到数据集（注册）中[像这样：new_name = print(Who is this?)]。然后我可以通过输入的名称创建一个新文件夹，并将面部存储在框架内。这就是我所做的：
new_name = input("Who is this?")
path_2 = os.path.join('Images',new_name)
os.mkdir(path_2)
print("Directory '% s' created" % new_name)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0,0,255),
thickness = 2)
cv2.putText(frame, new_name, (x, y), cv2.FONT_HERSHEY_SIMPLEX,
0.75, (0, 255, 0), 2)
sub_face = frame[y:y+h, x:x+w]
FaceFileName = new_name + str(y+x) + ".jpg"
cv2.imwrite(os.path.join(path_2,FaceFileName),sub_face)
cv2.imshow("Frame",frame)
#if cv2.waitKey(1) & 0xFF == ord('q'):
# break
这对新人来说效果很好。但现在我不得不为认识的人无法识别的面孔做些事情。 在这种情况下，我们已经有了输入名称的文件夹。我们必须通过输入的名称将图像附加到现有文件夹中。 因此，为此我尝试了以下代码：（不起作用）
else: # To store the unknown new face with name
new_name = input("Who is this?")
# If the new_name entered already exists as a folder
if os.path.isfile(new_name):
print(new_name,"folder already exists")
frame = imutils.resize(frame, width = 400)
rects = detector.detectMultiScale(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY),
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30))
FaceFileName = new_name + str(y+x) + ".jpg"
for (x, y, w, h) in rects:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.imshow("Frame",frame)
key = cv2.waitKey(1) & 0xFF
if key == ord("k"):
p = os.path.join([new_name,FaceFileName.format(str(total).zfill(5))])
# cv2.imwrite(os.path.join(path_2,FaceFileName),sub_face)
cv2.imwrite(p, orig)
total += 1
print("Image saved")
elif key == ord("q"):
break
# If the new_name does not exist as a folder new folder has to be created
else:
path_2 = os.path.join('Images',new_name)
os.mkdir(path_2)
print("Directory '% s' created" % new_name)
frame = imutils.resize(frame, width = 400)
rects = detector.detectMultiScale(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY),
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30))
FaceFileName = new_name + str(y+x) + ".jpg"
for (x, y, w, h) in rects:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.imshow("Frame",frame)
key = cv2.waitKey(1) & 0xFF
if key == ord("k"):
p = os.path.join([path_2,FaceFileName.format(str(total).zfill(5))])
# cv2.imwrite(os.path.join(path_2,FaceFileName),sub_face)
cv2.imwrite(p, orig)
total += 1
print("Image saved")
我收到错误：
Who is this?Vishwesh
Traceback (most recent call last):
File "C:\Users\Vishw\databs.py", line 117, in <module>
os.mkdir(path_2)
FileExistsError: [WinError 183] Cannot create a file when that file already exists: 'Images\\Vishwesh'
[ WARN:0] global C:\Users\runneradmin\AppData\Local\Temp\pip-req-build-sgoydvi3\opencv\modules\videoio\src\cap_msmf.cpp (438) `anonymous-namespace'::SourceReaderCB::~SourceReaderCB terminating async callback
完整代码如下。让我知道代码有什么问题。请帮忙！
注意：我将上述代码包含在 #Face识别 on LIVE WEBCAM FEED 部分以及“if True inmatches:”的 else 语句中：
这是我的完整代码：
# Extracting features from face
from imutils import paths
import face_recognition
import pickle
import cv2
import os
#Get paths of each file in folder named Images
#Images here contains my data(folders of various persons)
imagePaths = list(paths.list_images('Images'))
knownEncodings = []
knownNames = []
# loop over the image paths
for (i, imagePath) in enumerate(imagePaths):
# extract the person name from the image path
name = imagePath.split(os.path.sep)[-2]
# load the input image and convert it from BGR (OpenCV ordering)
# to dlib ordering (RGB)
image = cv2.imread(imagePath)
rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
#Use Face_recognition to locate faces
boxes = face_recognition.face_locations(rgb,model='hog')
# compute the facial embedding for the face
encodings = face_recognition.face_encodings(rgb, boxes)
# loop over the encodings
for encoding in encodings:
knownEncodings.append(encoding)
knownNames.append(name)
#save emcodings along with their names in dictionary data
data = {"encodings": knownEncodings, "names": knownNames}
#use pickle to save data into a file for later use
f = open("face_enc", "wb")
f.write(pickle.dumps(data))
f.close()
# Face recognition on LIVE WEBCAM FEED
import face_recognition
import pickle
import cv2
import os
#find path of xml file containing haarcascade file
cascPathface = os.path.dirname(
cv2.__file__) + "/data/haarcascade_frontalface_default.xml"
# load the harcaascade in the cascade classifier
faceCascade = cv2.CascadeClassifier(cascPathface)
# load the known faces and embeddings saved in last file
data = pickle.loads(open('face_enc', "rb").read())
print("Streaming started")
video_capture = cv2.VideoCapture(0)
# loop over frames from the video file stream
while True:
# grab the frame from the threaded video stream
ret, frame = video_capture.read()
orig = frame.copy()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = faceCascade.detectMultiScale(gray,
scaleFactor=1.05,
minNeighbors=3,
minSize=(60, 60),
flags=cv2.CASCADE_SCALE_IMAGE)
# convert the input frame from BGR to RGB
rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
# the facial embeddings for face in input
encodings = face_recognition.face_encodings(rgb)
names = []
# loop over the facial embeddings incase
# we have multiple embeddings for multiple fcaes
for encoding in encodings:
#Compare encodings with encodings in data["encodings"]
#Matches contain array with boolean values and True for the embeddings it matches closely
#and False for rest
matches = face_recognition.compare_faces(data["encodings"],encoding)
#set name =unknown if no encoding matches
name = "Unknown"
# check to see if we have found a match
if True in matches:
# Find positions at which we get True and store them
matchedIdxs = [i for (i, b) in enumerate(matches) if b]
counts = {}
# loop over the matched indexes and maintain a count for
# each recognized face face
for i in matchedIdxs:
#Check the names at respective indexes we stored in matchedIdxs
name = data["names"][i]
#increase count for the name we got
counts[name] = counts.get(name, 0) + 1
#set name which has highest count
name = max(counts, key=counts.get)
else: # To store the unknown new face with name
new_name = input("Who is this?")
# If the new_name entered already exists as a folder
if os.path.isfile(new_name):
print(new_name,"folder already exists")
frame = imutils.resize(frame, width = 400)
rects = detector.detectMultiScale(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY),
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30))
FaceFileName = new_name + str(y+x) + ".jpg"
for (x, y, w, h) in rects:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.imshow("Frame",frame)
key = cv2.waitKey(1) & 0xFF
if key == ord("k"):
p = os.path.join([new_name,FaceFileName.format(str(total).zfill(5))])
# cv2.imwrite(os.path.join(path_2,FaceFileName),sub_face)
cv2.imwrite(p, orig)
total += 1
print("Image saved")
elif key == ord("q"):
break
# If the new_name does not exist as a folder new folder has to be created
else:
path_2 = os.path.join('Images',new_name)
os.mkdir(path_2)
print("Directory '% s' created" % new_name)
frame = imutils.resize(frame, width = 400)
rects = detector.detectMultiScale(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY),
scaleFactor=1.1,
minNeighbors=5,
minSize=(30, 30))
FaceFileName = new_name + str(y+x) + ".jpg"
for (x, y, w, h) in rects:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.imshow("Frame",frame)
key = cv2.waitKey(1) & 0xFF
if key == ord("k"):
p = os.path.join([path_2,FaceFileName.format(str(total).zfill(5))])
# cv2.imwrite(os.path.join(path_2,FaceFileName),sub_face)
cv2.imwrite(p, orig)
total += 1
print("Image saved")
# update the list of names
names.append(name)
# loop over the recognized faces
for ((x, y, w, h), name) in zip(faces, names):
# rescale the face coordinates
# draw the predicted face name on the image
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 2)
cv2.putText(frame, name, (x, y), cv2.FONT_HERSHEY_SIMPLEX,
0.75, (0, 255, 0), 2)
cv2.imshow("Frame", frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
video_capture.release()
cv2.destroyAllWindows()
答案 0 :(得分：2)
因此，您的问题与文件操作有关，而与人脸识别有关... 在尝试创建文件夹之前尝试检查它是否已经存在：
path_2 = os.path.join('Images',new_name)
if not os.path.exists(path_2):
os.mkdir(path_2)
答案 1 :(得分：0)
使用@Bohdan 给出的想法：
else: # To store the unknown new face with name
new_name = input("Who is this?")
path_2 = os.path.join('Images',new_name)
for (x, y, w, h) in faces:
cv2.rectangle(frame, (x, y), (x + w, y + h), (0,0,255),
thickness = 2)
cv2.putText(frame, new_name, (x, y), cv2.FONT_HERSHEY_SIMPLEX,
0.75, (0, 255, 0), 2)
sub_face = frame[y:y+h, x:x+w]
FaceFileName = new_name + str(y+x) + ".jpg"
if not os.path.exists(path_2):
os.mkdir(path_2)
print("Directory '% s' created" % new_name)
cv2.imwrite(os.path.join(path_2,FaceFileName),sub_face)
# To store unrecognised faces of known people
else:
cv2.imwrite(os.path.join(path_2,FaceFileName),sub_face)
代码运行良好！